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| Criterion |  Engineering Failure Scenario Analysis |  Growth Growth Experiment |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Medium | Medium | Low | High |
Timedifferent | 1-3 h | 1-2 Wochen | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-8 | 1-6 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Experiment card, Result summary, Next bet | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | FailureResilienceRisk | MarketingGrowthExperimentsLearning | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |